Golf athleticism rating system

ABSTRACT

Aspects of this disclosure relate to systems and methods for rating the performance of an athlete, particularly a golf athlete. The systems and method may include instructing the user to perform multiple golf-relevant athleticism drills or tests such as a stepping exercise, a broad jump, a wood-chop bounce, a countermovement lateral hop and/or a side-sling object launch. One or more drills or tests may be performed in a hip-neutral manner so as to simulate a golfer&#39;s stance. The performance data collected from each of these tests may be input into a processing system to generate an athleticism rank and score for each test as well as an overall, multi-factorial rating of golf athleticism.

CROSS REFERENCE TO RELATED APPLICATIONS

This application, having attorney docket number NIKE.172005, is aContinuation-in-Part of copending U.S. Nonprovisional application havingSer. No. 12/559,082, attorney docket number NIKE.170315, filed on Sep.14, 2009, and entitled “Athletic Performance Rating System,” whichclaims the benefit of U.S. Provisional Patent Application No.61/096,603, filed on Sep. 12, 2008, entitled “Athletic PerformanceRating System.” The entireties of the aforementioned applications areincorporated by reference herein.

TECHNICAL FIELD

Aspects described herein relate to athleticism ratings and relatedperformance measuring systems, methods, apparatuses and the like. Inparticular, aspects are directed to athleticism ratings and performancemeasuring systems for determining golf athleticism for an individual orgroup.

BACKGROUND

Athletics contribute to the promotion of physical activity and a healthysense of competition. Commercially, athletics play a significant role inproviding entertainment to fans and generating revenue for the variousleagues and players. At any level of athletics, teams, sponsors, coachesand the like seek out the best athletes. However, evaluating anathlete's level of skill or potential is often very subjective. Forexample, in some instances, scouts or other evaluation personnel relyupon subjective and individual-specific opinions and experiencesregarding performance and the relative importance of various attributesof performance.

Some current systems attempt to use objective standards to evaluateathletic potential. Oftentimes, the systems use the same data and sameathletic exercises or tests regardless of the type of athletic activityfor which the athlete is being evaluated.

The present invention seeks to overcome certain limitations and otherdrawbacks, and to provide new features not heretofore available.

BRIEF SUMMARY

The following presents a general summary of aspects of the invention inorder to provide a basic understanding of the invention and variousfeatures of it. This summary is not intended to limit the scope of theinvention in any way, but it simply provides a general overview andcontext for the more detailed description that follows.

The present invention generally relates to systems and methods forrating the performance of an athlete, particularly a golf athlete usingvarious types of exercises and tests. In some arrangements, the tests orexercises may be specific to evaluating golf athleticism. Additional oralternatively, aspects described herein may include a portable testfield or mat that may be used to perform the various exercises or testsfor determining athleticism of an individual.

These and other features of the invention will become apparent from thefollowing detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of various aspects disclosed herein andcertain advantages thereof may be acquired by referring to the followingdetailed description in consideration with the accompanying drawings, inwhich:

FIG. 1 illustrates a general operating environment in which one or moreaspects described herein may be included.

FIG. 2 is a flowchart illustrating an exemplary method for collectingdata for generating an athleticism rating of an athlete based on a setof athletic exercises or tests according to one or more aspectsdescribed herein.

FIG. 3 is an exemplary graph illustrating rankings of performances in aparticular type of exercise among an athlete pool according to one ormore aspects described herein.

FIG. 4 is an exemplary table illustrating scoring values for an athletealong with possible scoring values according to one or more aspectsdescribed herein.

FIG. 5 is a table illustrating an example set of athleticism scores forvarious athleticism tests performed by an athlete according to one ormore aspects described herein.

FIG. 6 is a table illustrating an example set of athleticism scorescorresponding to ceiling values for various athleticism tests accordingto one or more aspects described herein.

FIG. 7 is a flowchart illustrating an exemplary method for generating anathleticism rating according to one or more aspects described herein.

FIG. 8 is a timeline and process flow illustrating a method forperforming a step test according to one or more aspects describedherein.

FIGS. 9A-9C illustrate an example athletic activity exercise that may beused to determine a golf athleticism rating according to one or moreaspects described herein.

FIGS. 10A and 10B illustrate another example athletic activity exercisethat may be used to determine a golf athleticism rating according to oneor more aspects described herein.

FIGS. 11A-11C illustrate another example athletic activity exercise thatmay be used to determine a golf athleticism rating according to one ormore aspects described herein.

FIGS. 12A-12C illustrate another example athletic activity exercise, awood-chop bounce, that may be used to determine a golf athleticismrating according to one or more aspects described herein.

FIGS. 13A-13D illustrate another example athletic activity exercise, aside-sling object launch, that may be used to determine a golfathleticism rating according to one or more aspects described herein.

FIGS. 14A and 14B illustrate an example exercise test field that may beused to perform one or more athleticism exercises/tests according to oneor more aspects described herein.

The reader is advised that the attached drawings are not necessarilydrawn to scale.

DETAILED DESCRIPTION

In the following description of various example structures and methodsin accordance with the invention, reference is made to the accompanyingdrawings, which form a part hereof, and in which are shown by way ofillustration various performance rating devices and systems usingperformance ratings or measuring devices in accordance with variousembodiments of the invention. Additionally, it is to be understood thatother specific arrangements of parts and structures may be utilized andstructural and functional modifications may be made without departingfrom the scope of the invention.

A first aspect of the present invention is directed to a system forperforming a method, the method including receiving athletic performanceresults from multiple types of performance tests. In an exemplaryaspect, the athletic performance results including at least two selectedfrom the following 1) a change in pulse of an athlete measured during astepping exercise, 2) a broad jump distance of an athlete, 3) a lateralhop distance of an athlete, 4) a bounce distance of a ball when thrownby the athlete in a downward direction toward a target, and 5) a slingdistance of a ball when thrown by the athlete using a underhanded sidesling. It is understood that when it is stated herein that at least twoare selected from the following, it is intended that at least twodifferent performance test are selected from the listing of possibleperformance tests. The method also comprised of generating, by thecomputing system, a golf athleticism rating based on the at least twoathletic performance results.

A second aspect of the present invention is directed to non-transitorycomputer readable media having computer-executable instructions embodiedthereon that when executed by a processor perform a method forevaluating the athleticism of an athlete in golf, The method comprisesreceiving at least two results for the athlete's performance in at leasttwo different athletic performance tests related to golf. The methodfurther comprises comparing each of the at least two results to acorresponding distribution of test results of athletic data for athletessimilar to the athlete and determining a percentile ranking for each ofthe at least two results. The method is further comprised oftransforming the percentile ranking for each of the at least two resultsto a fractional event point number for each result. The percentilerankings for each of the at least two results are progressive. Themethod further comprising determining an athleticism rating score forthe athlete in golf based on the fractional event point numbers.

FIG. 1 is a block diagram of an athleticism measurement system 100 thatincludes a sensor 102 (e.g., an accelerometer, compression sensor,inertial measurement system, etc.) that is borne by an athlete duringdifferent athletic drills or tests to generate data that are used togenerate an athleticism rating, such as a rating described inInternational patent application no. PCT/US2005/040493 for AthleticismRating and Performance Measuring Systems and incorporated herein byreference. Sensor 102 may be any type of sensor configured to detect astimulus and provide a resulting signal. In one embodiment, sensor 102may be configured to detect a force, such as an impact force from aperson or object striking another person or object. In certainembodiments, sensor 102 may be utilized to measure one or moreparameters, such as, for example, velocity, acceleration, pressure,location, energy transfer, temperature, orientation, light, sound,magnetism, or a particular motion along two or more axes. In oneembodiment, sensor 102 may comprise an accelerometer module. In aparticular example, the accelerometer module may be implemented with atwo-axis accelerometer for measuring acceleration along two orthogonalaxes. In another embodiment, the accelerometer module may be implementedwith a three-axis accelerometer for measuring acceleration along threeorthogonal axes.

Further exemplary sensors include strain gauges, conductive ink,piezo-electric devices and/or pressure transducers. In certainembodiments, relative pressure applied to sensor 102 (e.g., versuspressure detected by another sensor or by different components of sensor102) can be used to indicate weight distribution. In certainembodiments, sensor 102 may comprise a camera. A camera may detect ormeasure one or more properties of an athlete or other user, before,during or after, any processes or routines disclosed herein.Additionally, multiple sensors may be used in measuring an athlete'sperformance during one or more athleticism exercises or tests. Themultiple sensors may be of the same type or may include different types.In one example, the multiple sensors may correspond to accelerometersplaced at different locations on a test field or on an athlete's body.In another example, a first sensor may comprise an accelerometer whileanother sensor may comprise a pulse measurement sensor. Multiple sensorsmay be incorporated into the same physical device or may each bephysically separate from the others.

Acceleration sensor 102 may be positioned in a shoe, on top of a shoe,fastened around the ankle or wrist, attached to waist belts orincorporated into apparel on the body of the athlete, or otherwise borneby the athlete. For example, sensor 102 may be worn or attached to anyother portion of an athlete's body and/or incorporated into clothing asnecessary or desired. For example, an athlete may wear a sensor aroundhis or her head to measure head movement. In another example, an athletemay wear a shirt having a heart rate monitor included therein.

In an embodiment, sensor 102 communicates over a link 104 with anathleticism rating processing device 106. In one implementation, link104 is a wireless, digital, low-power RF link with 1-way or 2-waytransmission. A wired link could alternatively be employed in someapplications. Athleticism rating processing device 106 may include oneor more of an athleticism timing system, such as an electronic timingsystem, or a stopwatch, sport watch, digital music player, mobile phone,wireless athleticism measurement kiosk, etc. configured to communicateover link 104 with sensor 102.

According to one or more arrangements, athleticism rating processingdevice 106 allows a user (e.g., an athlete, coach, etc.) to select anathleticism measurement mode from among multiple selectable athleticismmeasurement modes. During a measurement mode, athleticism ratingprocessing device 106 obtains and stores acceleration data from sensor102 and selected timing data. In addition, athleticism rating processingdevice 106 may cue the athlete to perform certain actions during anathleticism measurement or may provide feedback during or after themeasurement.

In one implementation, athleticism rating processing device 106 deliversthe acceleration data and the timing data by wired or wirelesscommunication to an athleticism rating computer system 108 thatcalculates an athleticism rating based in part on the sensed data and/ortiming data. Athleticism rating computer system 108 may be disposed atthe location where the athlete performs the athletic drills or tests ormay be located remotely and accessed over a computer network (e.g., theInternet). In an alternative implementation, athleticism ratingprocessing device 106 may calculate an athleticism rating directly. Insome arrangements, athleticism rating processing device 106 and/orathleticism rating computer system 108 may be included as part of thesame physical device as sensor 102. For example, sensor 102 may includea processor and memory storing instructions for processing theathleticism data and subsequently calculating an athleticism rating. Inother arrangements, athleticism rating processing device 106,athleticism rating computer system 108 and sensor 102 may all correspondto physically separate devices. In yet other arrangements, processingdevice 106 and rating computer system 108 may correspond to a singlephysical computing device or system. Any of the sensor 102, processingdevice 106 and computer system 108 may also be configured to operate inmultiple modes, each mode corresponding to a different sport, type ofathletic activity, type of athleticism rating being determined and thelike. An example multi-mode athleticism movement measurement system isdescribed in further detail in U.S. Application Pub. No. 2008/0249736A1, entitled “MULTI-MODE ACCELERATION-BASED ATHLETICISM MEASUREMENTSYSTEM,” and filed on Sep. 28, 2007, which is hereby incorporated byreference in its entirety.

Processing device 106 (and/or computer system 108 and sensor 102) mayinclude one or more computing devices and components. For example,processing device 106 may include a computing unit 113. The computingunit 113 includes a processing unit 115 and a system memory 117. Theprocessing unit 115 may be any type of processing device for executingsoftware instructions, but will conventionally be a microprocessordevice. In some arrangements, processing unit 115 may be single-core ormulti-core. The system memory 117 may include both a read-only memory(ROM) 119 and a random access memory (RAM) 121. As will be appreciatedby those of ordinary skill in the art, both the read-only memory (ROM)119 and the random access memory (RAM) 121 may store softwareinstructions for execution by the processing unit 115. Further, it iscontemplated that one or more forms of memory may be non-transitorycomputer readable media.

The processing unit 115 and the system memory 117 are connected, eitherdirectly or indirectly, through a bus 123 or alternate communicationstructure to one or more peripheral devices. For example, the processingunit 115 or the system memory 117 may be directly or indirectlyconnected to additional memory storage, such as the hard disk drive 127and the optical disk drive 129. Other types of memory may also be used,including flash memory and removable magnetic drives. The processingunit 115 and the system memory 117 also may be directly or indirectlyconnected to one or more input devices 131 and one or more outputdevices 133. The input devices 131 may include, for example, a keyboard,touch screen, a remote control pad, a pointing device (such as a mouse,touchpad, stylus, trackball, or joystick), a scanner, a camera or amicrophone. The output devices 133 may include, for example, a monitordisplay, television, printer, stereo, or speakers.

Still further, the computing unit 113 will be directly or indirectlyconnected to one or more network interfaces 125 for communicating with anetwork. This type of network interface 125, also sometimes referred toas a network adapter or network interface card (NIC), translates dataand control signals from the computing unit 113 into network messagesaccording to one or more communication protocols, such as theTransmission Control Protocol (TCP), the Internet Protocol (IP), and theUser Datagram Protocol (UDP). Network adapters may be wireless or wiredor combinations thereof. These protocols are well known in the art, andthus will not be discussed here in more detail. A network interface 125may employ any suitable connection agent for connecting to a network,including, for example, a wireless transceiver, a power line adapter, amodem, or an Ethernet connection. Connection agents may similarly bewireless or wired or a combination thereof.

Using the system 100, a golf athleticism rating may be determined basedon a battery of tests and exercises that may, in one or morearrangements, be specific to potential in the golfing arena. Forexample, a user's performance during the tests and exercises may bemeasured using sensors such as sensor 102, collected by a processingdevice such as processing 106 and used to generate an athleticism ratingby a computing device such as computing system 108. In embodiments, oneor more of the performance results may be measured manually and entered,for instance, into input device 131 of processing device 106.Additionally, it is contemplated that one or more performance resultsmay be measured automatically and provided to the processing device 106,in an exemplary aspect.

FIG. 2 illustrates an exemplary method 200 whereby a computing devicemay detect and/or receive data corresponding to an athlete's performancefor one or more golf exercises and tests and generate an athleticismrating based thereon. In step 202, for example, athlete information maybe received by the computing system. The athlete information may includename, gender, age, height, weight, left/right-handedness, shoe size,wingspan, and the like. This information may be used in calculatingperformance in a particular test or exercise. For example, if acomputing system seeks to determine an athlete's leg strength, thecomputing system may use the athlete's weight in combination with theathlete's vertical jump height to determine leg strength or power. Inanother example, shoe size may be used to insure proper foot placementfor a particular test or exercise. In a particular example, if a testrequires that one foot is placed behind the other without overlap, asystem may determine if this condition has been satisfied by detecting aheel edge of a user's foot wear and determining, using the athlete'sshoe size, whether the toe point of the foot overlaps the heel edge ofthe user's other foot. An athlete's information may also be used tocategorize the data. For example, the athlete's gender may be used todetermine a pool of data in which to store the athlete's performancedata. The various pools of data may be used as the basis for generatingathleticism ratings. Thus, athleticism ratings for male and femaleathletes may correspond to different scales and athlete pools and thus,might not be directly comparable.

In step 205, the computing system may determine a series of one or moretests or exercises for the athlete. The series of tests or exercises maybe selected based on the athlete information. For example, someexercises or tests might not be age-appropriate for younger athletes. Ina particular example, a dunking test for basketball might not beappropriate or valuable for athletes under the age of 14 due to height,muscular development and other issues. Tests and exercises might also besport-specific or athletic activity-specific. In a present embodiment,for instance, tests and exercises might be specific to golf. Exampletests and exercises for evaluating golf athleticism are described infurther detail below. In other arrangements, some exercises may begeneric to multiple sports, but a set of exercises or tests are specificor unique to a given sport or athletic activity. Moreover, tests andexercises or sets of tests or exercises may be gender specific.

In step 210, the computing system may provide instructions on when andhow to perform each exercise. In some examples, the computing system mayprovide audible, visual or haptic cues to indicate times at which aparticular movement or action is expected. In a particular example, anaudible and/or visible cue may be provided when a user is expected tojump or throw an object. Instructions may further include an animationillustrating the type of movement expected for the test. The computingsystem may progress through the set of exercises and tests, instructingthe athlete through each one. In step 215, the computing mayconcurrently and/or subsequently request and receive performance data.For example, the computing system may, based on the determined exerciseor set of exercises, generate requests for particular types of data suchas a number of steps taken, a top speed, a distance an object wasthrown, a distance the athlete moved, or an impact force (e.g., force ofthe athlete hitting the ground or another object, of an object beingthrown or otherwise propelled by the athlete and the like). In oneparticular example, the computing system may generate an interfaceincluding a data entry form. The data entry form may include fields forparticular types of performance data based on the types of exercises andtests performed. Thus, if an exercise or a set of exercises is unique toa type of sport or athletic activity, the data requested by the computersystem (and, in some examples, the data entry form) may also be uniqueto the sport or athletic activity. Various types of data are describedin additional detail below.

Upon receiving the athletic performance data, the computer system may,in step 220, generate an athleticism score or value for eachtest/exercise by comparing the athlete's performance data with data froma pool of other athletes for the particular test/exercise. Based on theathlete's athleticism score for each test/exercise, an overallathleticism rating for an athletic activity or sport such as golf may bedetermined in step 225. In one example, a number of points may bedetermined for each exercise or test and the points later combined.Either the overall athleticism rating or the exercise-specific scores orboth may also be scaled. The athleticism rating may thus represent alevel of potential or skill in a particular athletic activity (e.g.,sport-specific athleticism rating) relative to an athlete pool.Accordingly, athleticism ratings may be comparable within the athletepool, but might not be comparable outside of the pool. In somearrangements, the athleticism ratings may be comparable between multipleor all athlete pools.

According to one or more configurations, determining an athleticismrating may include two general steps: 1) normalization of raw scores(e.g., test data) and 2) converting normalized scores to accumulatedpoints. Normalization may be a prerequisite for comparing data fromdifferent tests. Step 1 ensures that subsequent comparisons aremeaningful while step 2 determines the specific facets of the scoringsystem (e.g., is extreme performance rewarded progressively or arereturns diminishing). Because the mapping developed in step 2 convertsnormalized test results to (fractional event) points in a standardizedfashion, this scoring method can be applied universally to all tests,regardless of sport and/or measurement scale. Prudent choice ofnormalization and transformation functions provides a consistent ratingto value performance according to predetermined properties.

In order to compare results of different tests comprising the set orbattery of tests for a particular sport such as golf, the results may bestandardized on a common scale. If data is normal, a commonstandardization is the z-score, which represents the (signed) number ofstandard deviations between the observation and the mean value. However,when data are non-normal, z-scores are no longer appropriate as they donot have consistent interpretation for data from differentdistributions. A more robust standardization is the percentile of theempirical cumulative distribution function (ECDF), u, defined asfollows:

${u = {\frac{1}{n + 1}\left\lbrack {{\sum\limits_{j}\left( {{{II}\left\{ {y_{j} < x} \right\}} + {\frac{1}{2}{II}\left\{ {y_{j} = x} \right\}}} \right)} + \frac{1}{2}} \right\rbrack}},$

In the above equation, x is the raw measurement to be standardized; y₁,y₂, . . . y_(n) are the data used to calibrate the event and II{A} is anindicator function equal to 1 if the event A occurs and 0 otherwise.Note that u depends on both the raw measurement of interest, x, and theraw measurements of peers, y.

The addition of ½ to the summation in square brackets and the use of(n+1) in the denominator ensures that uε(0, 1) with strict inequality.Although the definition is cumbersome, u is calculated easily byordering and counting the combined data set consisting of allcalibration data (y₁, y₂, . . . , y_(n)) and the raw score to bestandardized, x.

$\begin{matrix}{u = \frac{\left\lbrack {\# \mspace{14mu} {of}\mspace{14mu} y^{\prime}s\mspace{14mu} {less}\mspace{14mu} {than}\mspace{14mu} x} \right\rbrack + {0.5\left\lbrack {\left( {\# \mspace{14mu} {of}\mspace{14mu} y^{\prime}s\mspace{14mu} {equal}\mspace{14mu} {to}\mspace{14mu} x} \right) + 1} \right\rbrack}}{{\# \mspace{14mu} {of}\mspace{14mu} y^{\prime}s} + 1}} \\{= \frac{\left\lbrack {\# \mspace{14mu} {of}\mspace{14mu} \left( {y^{\prime}s\mspace{20mu} {and}\mspace{14mu} x} \right)\mspace{14mu} {less}\mspace{14mu} {than}\mspace{14mu} x} \right\rbrack + {0.5\left\lbrack {\# \mspace{14mu} {of}\mspace{14mu} \left( {y^{\prime}s\mspace{14mu} {and}\mspace{14mu} x} \right)\mspace{14mu} {equal}\mspace{14mu} {to}\mspace{14mu} x} \right\rbrack}}{\# \mspace{14mu} {of}\mspace{14mu} \left( {y^{\prime}s\mspace{14mu} {and}\mspace{14mu} x} \right)}}\end{matrix}$

Note that this definition still applies to binned data (though raw datamay be used whenever possible).

Although the ECDFs calculated in step 1 provide a common scale by whichto compare results from disparate tests, the ECDFs may be inappropriatefor scoring performance because they do not award points consistentlywith progressive rewards and percentile “anchors” (sanity checks).Therefore, it is necessary to transform (via a monotonic, 1-to-1mapping) the computed percentiles into an appropriate point scale.

An inverse Weibull transformation provides such a transformation and isgiven by

${w = {\frac{1}{\lambda}\left\lbrack {- {\ln \left( {1 - u} \right)}} \right\rbrack}^{1/\alpha}},{{{where}\mspace{14mu} \alpha} = {{1.610\mspace{14mu} {and}\mspace{14mu} \lambda} = {2.512.}}}$

The above function relies on two parameters α and λ and produces scoringcurves that are qualitatively similar to the two-parameter power-lawapplied to raw scores. The parameters α and λ were chosen to satisfyapproximately the following four rules governing the relationshipbetween percentile of performance and points awarded:

-   -   1. The 10th percentile should achieve roughly ten percent of the        nominal maximum.    -   2. The 50th percentile should achieve roughly thirty percent of        the nominal maximum.    -   3. The 97.7th percentile should achieve roughly one hundred        percent of the nominal maximum.    -   4. The 99.9th percentile should achieve roughly one hundred        twenty-five percent of the nominal maximum.

Because, in general, four constraints cannot be satisfied simultaneouslyby a two-parameter model, parameters were chosen to minimize somemeasure of discrepancy (in this case the sum of squared log-errors).However, estimation was relatively insensitive to the specific choice ofdiscrepancy metric.

To illustrate the method when raw (unbinned) data is available, considerscoring three performances, 12, 16, and 30, using a calibration data setconsisting of nine observations: 16, 20, 25, 27, 19, 18, 26, 27, and 15.

For x=16, there is one observation in the calibration data (15) that isless than x and one that is equal. Therefore,

$u = {{\frac{1}{9 + 1}\left\lbrack {{\sum\limits_{j}\left( {{{II}\left\{ {y_{j} < 16} \right\}} + {\frac{1}{2}{II}\left\{ {y_{j} = 16} \right\}}} \right)} + \frac{1}{2}} \right\rbrack} = {{\frac{1}{10}\left\lbrack {1 + \frac{1}{2} + \frac{1}{2}} \right\rbrack} = {0.20.}}}$

A summary of calculations is given in the following table.

x Σ_(j) Π(y_(j) < x) Σ_(j) Π(y_(j) = x) u w 12 0 0 [0 + (0.5)(0) +0.5]/(9 + 1) = 0.063 0.05 16 1 1 [1 + (0.5)(1) + 0.5]/(9 + 1) = 0.1570.20 30 9 0 [9 + (0.5)(0) + 0.5]/(9 + 1) = 0.787 0.95

For backward compatibility, it may be necessary to score athletes basedon binned data. Consider scoring four performances, 40, 120, 135, and180, using a calibration data set binned as follows. Here, the bin labelcorresponds to the lower bound, e.g., the bin labeled 90 containsmeasurements from the interval (90, 100).

Bin Count <50 0  50 2  60 19  70 33  80 63  90 39 100 20 110 17 120 26130 14 140 4 150 3 160 1 170 4 Total 245

For x=135, there are 0+2++17+26=219 observations that are in bins lessthan the one that contains x and 14 that fall in the same bin.Therefore,

$\begin{matrix}{u = {\frac{1}{245 + 1}\left\lbrack {{\sum\limits_{j}\begin{pmatrix}{{{II}\left\{ {y_{j} < {{bin}\mspace{14mu} {containing}\mspace{14mu} 135}} \right\}} +} \\{\frac{1}{2}{II}\left\{ {y_{j}\mspace{14mu} {in}\mspace{14mu} {bin}\mspace{14mu} {containing}\mspace{14mu} 135} \right\}}\end{pmatrix}} + \frac{1}{2}} \right\rbrack}} \\{= {\frac{1}{246}\left\lbrack {219 + 7 + \frac{1}{2}} \right\rbrack}} \\{= {0.921.}}\end{matrix}$

A summary of calculations is given in the following table.

x Σ_(j) Π{y_(j) < x} Σ_(j) Π{y_(j) = x} u w 40 0 0 0.002 0.008 120 19326 0.839 0.579 135 219 14 0.921 0.709 180 241 4 0.990 1.026

The standardization and transformation processes are performed exactlyas in the raw data example; however, care must be taken to ensureconsistent treatment of bins. All raw values contained in the same binwill result in the same standardized value and thus the same score. Inshort, scoring based on binned data simplifies data collection andstorage at the expense of resolution (only a range, not a precise value,is recorded) and complexity (consistent treatment of bin labels).

In rare circumstances, only summary statistics (such as the mean andstandard deviation) of the calibration data are available. If anassumption of normal data is made, then raw data can be standardized inMicrosoft® Excel®, available from the Microsoft Corporation of Redmond,Wash., using the normsdist( ) function.

The above method relies heavily on the assumption of normality.Therefore if data are not normal it will, naturally, perform poorly. Dueto the assumed normality, this method does not enjoy the robustness ofthe ECDF method based on raw or binned data and should be avoided unlessthere is no other alternative.

To illustrate this technique, assume that the mean and standarddeviation of a normally distributed calibration data set are 98.48 and24.71, respectively, and it is desirable to score x=150. In this case,u=normsdist((150−98.48)/24.71)=0.981.

As before,

$\omega = {{\frac{1}{\lambda}\left\lbrack {- {\ln \left( {1 - u} \right)}} \right\rbrack}^{1/\alpha} = {{\frac{1}{2.512}\left\lbrack {- {\ln \left( {1 - 0.981} \right)}} \right\rbrack}^{1/1.610} = {0.924.}}}$

Once the norm data has been collected and sorted in a manner, as setforth above for a given test, its ECDF is scatter plotted to reveal thePerformance Curve. For example, non-standing vertical jump data observedin the field for 288 girls are shown as indicated in FIG. 3. For thoseresults not observed, e.g., 26.6 inches, that value's rank (99.37percentile) is assigned by interpolation; the unobserved pointsrequiring assigned ranks are shown as indicated in FIG. 3.

For each test, a “ceiling” and a “floor” value is determined, whichrepresent the boundaries of scoring for each test. Any test value at orabove the ceiling earns the same number of event points. Likewise, anytest value at or below the floor earns the same number of event points.These boundaries serve to keep the rating scale intact. The ceilinglimits the chance of a single exceptional test result skewing anathlete's rating, thereby masking mediocre performance in other tests.

Each rank is transformed to fractional event points using a statisticalfunction, as set forth above with respect to the inverse WeibullTransformation. The scoring curve of event points is shown for girls'no-step vertical jump in FIG. 3, as indicated therein, where the pointsare displayed as percentages, i.e., 0.50 points (awarded for a jump of18.1 inches) are shown as fifty percent. These fractional event pointsare also referred to as the w-score (“w” for Weibull).

The inverse Weibull Transformation can process non-normal (skewed)distributions of test data, as described above. The transformation alsoallows for progressive scoring at the upper end of the performancerange. Progressive scoring assigns points progressively (moregenerously) for test results that are more exceptional. Progressivescoring allows for accentuation of elite performance, thus making therating more useful as a tool for talent identification.

FIG. 4 identifies a sample athlete, “Andrea White” who jumped 26.5inches during a no-step vertical jump. This value corresponds to w-scoreof 1.078. The w-scores for all of her tests are found by referencingthose tests' respective look-up tables. These w-scores are shown in FIG.5.

The fractional event points are summed for each ratings test variable toarrive at the athlete's total w-score (5.520 in FIG. 5, for example).This total is multiplied by an event scaling factor to produce a rating.For a girls' basketball rating, for example, this scaling factor is 18,and so Andrea White's overall athleticism rating is 99.36 (=5.520×18).

The “event scaling factor” is determined for each rating by the numberof rated events and desired rating range. Ratings should generally fallwithin a range of 10 to 110. A boys' scaling factor is 25, for example,as the rating comprises four variables: Peak Power, Max Touch, LaneAgility, and three-quarter Court Sprint.

Were a female athlete to “hit the ceiling” on all six tests (shown inFIG. 6), her w-score total would yield a rating of almost 130 (129.85).

Assessing each of the various scores for each test provides the athletewith an overall athleticism rating, which may be used by the athlete incomparing their ability and/or performance to other athletes withintheir age group. Furthermore, the athlete may use such information tocompare their skill set with those of other athletes in a particularsport (e.g., basketball, golf, etc.) to determine how their skill setcompares with that of a professional athlete in the sport. While theabove described tests and data may relate more to basketball or othersimilar activities, the same or similar algorithms, formulas,calculations and processes may be used to develop ratings for tests andexercises relating to other sports such as golf.

FIG. 7 illustrates a method 700 for generating an athleticism ratingbased on performance data collected in multiple athletic exercises ortests. Initially, as indicated at step 702, athletic performance datarelated to a particular sport are collected for a group of athletes. Asdescribed herein, the performance data may correspond to multipledifferent athletic tests or exercises. In some arrangements, those testsor exercises may be specific or unique to a particular sport or type ofathletic activity/movement. Athletic performance data might include, byway of example, and not limitation, a no-step vertical jump height, anapproach jump reach height, a sprint time for a predetermined distance,a cycle time around a predetermined course, or the like. Athleticperformance data can be recorded for multiple athletes (e.g., a group ofhundreds or thousands of athletes).

In step 705, the collected athletic performance data, such as athleticperformance test results, may be normalized. Accordingly, athleticperformance test results (e.g., raw test results) for each athletic testperformed by an athlete in association with a defined sport arenormalized. That is, raw test results for each athlete can bestandardized in accordance with a common scale. Normalization enables acomparison of data corresponding with different athletic tests. In oneembodiment, a normalized athletic performance datum is a percentile ofthe empirical cumulative distribution function (ECDF). Any method can beutilized to obtain normalized athletic performance data (i.e., athleticperformance data that has been normalized).

In step 710, the normalized athletic performance data is utilized togenerate a set of ranks. The set of ranks includes an assigned rank foreach athletic performance test result included within a scoring table. Ascoring table (e.g., a lookup table) includes a set of athleticperformance test results, or possibilities (e.g., potential test valuesor results) thereof. Each athletic performance test result within ascoring table corresponds with an assigned rank and/or a fractionalevent point number. In one embodiment, the athletic performance data issorted and a percentile of the empirical cumulative distributionfunction (ECDF) is calculated for each value. As such, the percentile ofthe empirical cumulative distribution function represents a rank for aspecific athletic performance test result included in the scoring table.In this regard, each athletic performance test result is assigned aranking number based on that test result's percentile among the normaldistribution of test results. As such, the rank (e.g., percentile) maydepend on the raw test measurements and may be a function of both thesize of the data set and the component test values. As can beappreciated, a scoring table might include observed athletic performancetest results and unobserved athletic performance test results. A rankthat corresponds with an unobserved athletic performance test result canbe assigned using interpolation of the observed athletic performancetest data.

In step 715, a fractional event point number is determined for eachathletic performance test result. A fractional event point number for aparticular athletic performance test result is determined or calculatedbased on the corresponding assigned rank. That is, the set of assignedranks, or percentiles, is transformed into an appropriate point scale.In one embodiment, a statistical function, such as an inverse Weibulltransformation, provides such a transformation.

In step 720, one or more scoring tables are generated. As previouslymentioned, a scoring table (e.g., a lookup table) includes a set ofathletic performance test results, or possibilities thereof. Eachathletic performance test result within a scoring table corresponds withan assigned rank and/or a fractional event point number. In some cases,a single scoring table that includes data associated with multiple testsand/or sports can be generated. Alternatively, multiple scoring tablescan be generated. For instance, a scoring table might be generated foreach sport or for each athletic performance test. One or more scoringtables, or a portion thereof (e.g., athletic test results, assignedranks, fractional event point numbers, etc.) can be stored in adatabase.

In step 725, athletic performance data in association with a particularathlete is referenced (e.g., received, obtained, retrieved, identified,or the like). That is, athletic performance test results for a pluralityof different athletic performance tests are referenced. The set ofathletic tests can be predefined in accordance with a particular sportor other physical activity. An athletic performance test is designed toassess the athletic ability and/or performance of a given athlete andmeasures an athletic performance skill related to a particular sport ortype of physical activity.

At step 730, a fractional event point number that corresponds with eachtest result of the athlete is identified. Using a scoring table, afractional event point number can be looked up, determined, calculated,or recognized based on the athletic performance test result for theathlete. In some arrangements, the best result from each test istranslated into a fractional event point number by referencing the testresult in the lookup table for each test. Although the above describedprocess includes generating a scoring table having a rank and afractional event point number that corresponds with each test result touse to lookup a fractional event point number for a specific athleticperformance test result, alternative methods can be utilized to identifyor determine a fractional event point number for a test result. Forinstance, in some cases, upon receiving an athlete's test results, arank and/or a fractional event point number could be determined. In thisregard, an algorithm can be performed in real time to calculate afractional event point number for a specific athletic performance testresult. By way of example only, an athletic performance test result fora particular athlete can be compared to a distribution of test resultsof athletic data for athletes similar to the athlete, and a percentileranking for the test result can be determined. Thereafter, thepercentile ranking for the test result can be transformed to afractional event point number.

In step 735, the fractional event point number for each relevant testresult for the athlete is combined or aggregated to arrive at a totalpoint score. That is, the fractional event point number for each testresult for the athlete is summed to calculate the athlete's total pointscore. At step 740, the total point score is multiplied by an eventscaling factor to produce an overall athleticism rating. An eventscaling factor can be determined using the number of rated events and/ordesired rating range. Athletic data associated with a particularathlete, such as athletic test results, ranks, fractional event pointnumbers, total point values, overall athleticism rating, or the like,can be stored in a database.

While athleticism ratings may be developed for a variety of differentathletic activities, sports and movements, athleticism ratings for eachtype of athletic activity, sport and/or movement may be based ondifferent metrics, tests and athleticism exercises. In determining anathleticism rating for golf, for instance, a computing system mayrequest and/or receive input relating to endurance (e.g., using a par 5step test), leg power (e.g., through a broad jump exercise and/or acountermovement lateral hop test), rotational and throwing force (e.g.,based on a wood-chop bounce exercise and/or a side-sling launchexercise). The noted golf athleticism rating exercises or tests may moreaccurately measure an athlete's golf athleticism versus using othertypes of tests or exercises. In other arrangements, additional exercisesor tests may be added to the battery or set of golf athleticismexercises as desired.

FIG. 8 illustrates a process 800 for performing an endurance-based par 5step test. The test is intended to simulate the amount of exercise orphysical exertion involved in completing a par 5 hole on a golf course.In step 802, for example, a computing system may instruct a user toperform a pulse find over a predefined amount of time. That is, the usermay be asked, within a 30-second period, for example, to practice orattempt to find an athlete's pulse. The athlete may be the user or maybe another individual. This find period may also be used to allow anathlete's pulse to lower from peaks before taking a reading.

Upon expiration of the initial 30-second find period or other timeperiod, the computing system may subsequently instruct the user toperform a read of the subject athlete's pulse for a predefined pulseread time period in step 804. In one example, the predefined time periodmay be 30 seconds and a number of heart beats may be counted or detectedover the 30-second period and multiplied by 2 to result in a beats perminute (bpm) value. Alternatively, the counted value over the 30 secondperiod may be used for athleticism rating calculation purposes. Heartbeats may be determined through manual user counting/determination orusing electromechanical systems.

FIG. 9A illustrates an example process by which a pulse may be read. Forexample, an athlete 901 may measure the pulse of a subject athlete 903by placing their fingers along a wrist area of the subject athlete 903.The measuring athlete 901 may then count the number of beats over thepredefined time period. As illustrated, athletes 901 and 903 maysimultaneously or concurrently measure the pulse of the other athlete903 and 901, respectively. As previously provided, an electromechanicalheart rate monitor may be utilized as an alternative or in addition toother methods provided herein.

Referring again to FIG. 8, in step 806, after determining the subjectathlete's pulse (e.g., at the one minute mark from the start of theexercise), the computing system may instruct the user to record the datadetermined in step 806 and to begin practicing an athletic movement suchas stepping. In a particular example, the athletic movement may includewalking up and down a set of steps. Step 806 may last a total of 30seconds (or other predefined amount) of exercise time. Various timeperiods may be used and the time periods described herein with respectto each process step (e.g., read, find, rest, report, step, etc.) may bedifferent or equal to the time periods for each of the other processsteps. In some instances, the predefined amount of time corresponding tostep 806 may correspond to twice the predefined period of step 804.Alternatively, the predefined time period of step 806 may be threetimes, four times, ten times, (or any multiple, whole or fractional)etc. of the predefined period of step 804. Reporting may includerecording the data manually (e.g., on paper or other physical writingmedium) or entry into the computing system or a combination thereof.

The step test may include the setting or generation of a periodic oraperiodic beat (e.g., audible or visual) with which the user is tofollow with steps. In one example, the computing system may generate andproduce a periodic beat (audible, visual and/or haptic) having afrequency of 60 beats per minute. In another example, a metronome may beused to set the beat (the computing system may also provide instructionsto this effect). Other mechanical, electromechanical and manual methods(e.g., manually timing and counting out the beats) and systems may alsobe used to setting and/or cuing a user to a particular beat. Other beatfrequencies may also be used including 30 beats per minute, 25 beats perminute, 45 beats per minute, 120 beats per minute and the like. In somearrangements, the beat may be aperiodic. For example, the beat mayinclude a first beat at time 0, followed by a second beat at time 1second and a third beat at time 4 seconds and a fourth beat at time 10seconds.

During the practice phase, the computing system may further provideinstructions on the type of movement expected at each beat or cue. Forexample, the computing system may instruct the athlete to step up withthe left foot at the first beat, to step up with the right foot at thesecond beat, to step down with the left foot at the third beat and tostep down with the right foot at the fourth beat and so on (repeatingwith same set of steps or with other sets of step movements).Accordingly, the par 5 step test may require performance with or on aphysical structure having multiple elevations (e.g., a set of steps). Insome instances, only two levels or elevations are necessary while inother examples, more than two levels or elevations may be required.Other arrangements of step movements may also be used. For example, theathlete may be asked to perform right up, left up, right up, left up,right down, left down, right up, left up, right up, left up and so on.The instructions might also depend on the dominant foot of the athlete.For example, the athlete may be instructed to start with the dominantfoot first followed by the non-dominant foot.

Once the practice and report phase is completed (e.g., from step 806),the computing system may subsequently instruct the athlete to performactual steps (in contrast to practice steps) for a predefined amount oftime in step 808. In this arrangement, the predefined amount of steptime may be 3 minutes. As with the practice phase, the computing systemmay provide or instruct a user or other device such as a metronome toprovide an audible, visual (e.g., on a display) or haptic cue (e.g., abeat). In one example, the instructions may include an instruction for auser to activate a metronome or other beat generating device. Thecomputing system may further display or audibly convey the particularmovement required at each beat.

FIGS. 9B and 9C illustrate example stepping movements that may beperformed by athletes on a set of steps in conjunction with theexercise/test described in FIG. 8.

Referring again to FIG. 8, upon expiration of the stepping period inprocess step 808, the computing system may provide an instruction forthe subject athlete to stop the stepping movement and to beginperforming a pulse find in step 810. As described in step 802 and FIG.9A, a pulse find may include locating the subject's pulse, allowing thesubject's pulse to lower from a peak, and/or to otherwise prepare fordetermining the subject athlete's pulse. The pulse find process may beperformed over a predefined time period such as 30 seconds.

Once the pulse find time period has expired, the computing system maysubsequently instruct the user to read the subject athlete's pulse instep 812 over another predefined time period (e.g., 30 seconds, 1minute, 45 seconds, 10 seconds, 2 minutes, 5 minutes, etc.). In one ormore arrangements, read time periods and find time periods may be thesame. In other arrangements, these time periods may be different. In yetother arrangements, each read time period and/or each find time periodmay different from one or more of the other read time periods or findtime periods, respectively.

Next, the computing system may subsequently instruct the user to againperform a stepping exercise for another predefined amount of time instep 814. This second stepping phase may have a duration that is lessthan the first stepping phase (step 808). In one example, the firststepping phase may have a duration of three minutes while the secondstepping phase may have a duration of two minutes. The relationshipbetween the first stepping phase duration and the second stepping phaseduration may be defined in a number of ways. For example, the firststepping phase duration may be defined as one minute more than thesecond stepping phase duration. In other examples, the first steppingphase duration may be defined as twice, three times, 10 times, etc. thesecond stepping phase duration. In yet other examples, the secondstepping phase duration may be defined as a fraction of the firststepping phase duration (e.g., ½, ¾, ⅔, 3/7, etc.).

The second stepping phase of step 814 may be followed by, similar to thefirst stepping phase, a find phase of 30-seconds (or another duration)at step 816, and a read phase of 30-seconds (or another duration) atstep 818. Next, a computing system may instruct an athlete to perform athird stepping phase or round in step 820 for a predefined duration. Theduration of the third stepping phase may be related to the durations ofthe second stepping phase and the first stepping phase. For example, theduration of the third stepping phase may be 1 minute less than theduration of the second stepping phase (and two minutes less than theduration of the first stepping phase). Alternatively or additionally,the duration of the third stepping phase may be a predefined percentageor fraction of the durations of the first and/or second stepping phases.The movements required in the stepping phases may be the same (just fordifferent durations) or may vary. For example, in the first steppingphase, the athlete may be instructed to perform right step up, left stepup, right step up, left step up, right step down, etc. while in thesecond stepping phase, the athlete may be instructed to perform rightstep up, left step up, right step down, left step down. The thirdstepping phase may further be different from the first and secondstepping phases.

The third (and final in some examples) stepping phase 820 may befollowed a find phase of 30-seconds (or another duration) at step 816,and a read phase of 30-seconds (or another duration) at step 818.

The final report may be provided based on a user interface or electronicform generated by the computing system. The electronic form may bespecific to the par 5 test and request various information including thevarious pulse readings at the specified times. According to one or morearrangements, in addition to or alternatively, the computing system mayautomatically take the pulse measurements during the read phases. Inother arrangements, a user may perform the pulse reading process in amanual fashion (e.g., either by manually counting or using a device tomeasure the subject's pulse). By measuring the subject's pulse andchange in the subject's pulse after varying degrees (e.g., time oramount) of exercise (e.g. stepping) and rest, a computing system maydetermine the subject's endurance or ability to recover (e.g., based onthe changes or differences in pulse readings at the specified times).This information may be relevant to how well an athlete would perform(e.g., endurance-wise) in golf games since golf games tend to lastmultiple hours and require a significant amount of walking.

The data recorded during the above par 5 step test may be requested andreceived by the computing system in conjunction with a correspondinginstruction or may be requested and received at the end of the entiretest. Alternatively, data may be collected at various intervals orpoints during the test (e.g., during rest periods and the like).Additionally or alternatively, any number of stepping rounds may beperformed or required.

FIGS. 10A and 10B illustrate an example process for performing a broadjump test/exercise for evaluating golf athleticism. The broad jumpexercise may begin with an athlete 1001 being positioned with feet 1003parallel and toes (or tip of the athlete's shoe) placed at a predefinedpoint such as a baseline 1005 as illustrated in FIG. 10A. The athlete1001 may further be required to start in a crouched position inpreparation for launching himself or herself as far as possible in aspecified direction (e.g., direction A). In one or more arrangements, asensor system (not shown) may be deployed along baseline 1005 to insurethat the athlete's feet are properly aligned. For example, if theathlete 1001 crosses baseline 1005, the sensor may sound an alarm orother type of visual, audio or haptic alert/feedback cue. Additionallyor alternatively, if the athlete's toes are not touching baseline 1005,a test administrator and/or the athlete may be notified.

A computing system may further cue the athlete 1001 to begin theexercise. For example, the computing system may provide an audible,visual and/or haptic cue to begin a jump. Upon generating the cue,athlete 1001 may perform a broad jump. FIG. 10B illustrates athlete 1001mid-jump. Upon landing, the athlete 1001 may be required to remainupright with feet stationary so as to permit accurate measurement. Themeasurement may be taken from the baseline to the heel of athlete 1001closest to the baseline. In one example, the measurement may be takenthrough a manual process. In other examples, electronic sensors (e.g.,RFID, weight sensors, etc.) may be used to detect the position ofathlete 1001's feet. By determining the position of the athlete's feet,a system may determine a heel point of the athlete's back foot (e.g.,based on knowing the athlete's shoe size). This measurement may then beused to determine a broad jump athleticism score as described herein.

An athlete's jump may be disqualified, not recorded or not counted for avariety of reasons. For example, if the athlete steps into the jump, theathlete's jump may be disqualified. In another example, the athlete'sjump may be disqualified if the athlete's toes cross the baseline priorto the jump. In yet another example, disqualification may be based onthe athlete taking a step, hopping or landing any other body part otherthan his feet on the jumping surface within a 5-second period afterlanding and/or prior to confirmed measurement. In one or morearrangements, the athlete may be required to perform two qualifiedjumps. An average may then be taken as the final recorded jump value andscore. In other examples, the athlete might only be allowed to use asingle jump score. Accordingly, if the user's first or second jump isdisqualified, the athlete might be required to base his or herathleticism score for the broad jump on the other jump.

Another exercise or test that may be used to evaluate golf athleticismis a countermovement lateral hop test designed to measure leg power withweight transfer and stabilization upon landing. This test may be usedfor determining golf athleticism since FIGS. 11A-11C illustrate anexample countermovement lateral hop movement. A countermovement lateralhop corresponds to an athlete dominant-leg lateral hop to the oppositeleg, covering the greatest distance possible. In FIG. 11A, for instance,a user positions him or herself in an initial stance. The initial stancemay involve the athlete placing the lateral outside edge of his or herdominant foot 1103 along a baseline 1105 while standing with his or hershoulder line perpendicular to baseline 1105. The athlete's foot and/orbody position may be verified using various types of sensors such aslaser sensors, weight sensors, and/or computing systems to performvisual analysis of the athlete's position and the like.

Once the athlete has established his or her initial stance and theinitial stance has been verified as proper, the athlete may then be cuedor otherwise instructed to hop, leading with the non-dominant foot, asfar as possible in direction B. FIG. 11B illustrates an athleteinitiating a hop. The user may be encouraged or instructed to shift hisor her weight to the dominant foot before launching into the hop. Theathlete may be permitted to move either foot prior to the jump, but maybe required to touch the baseline 1105 with his or her dominant foot1103 just prior to initiating the jump/hop. Initiation of the hop may bedefined by the lifting of the dominant foot while the non-dominant footis in mid-air (i.e., not in contact with the test surface).

FIG. 11C illustrates an athlete's landing upon completing thecountermovement lateral hop. Once the athlete has landed, a measurementmay be taken between the baseline 1105 and an inside lateral edge 1107of the athlete's non-dominant foot (i.e., front/lead foot). Again, thismeasurement may be taken manually or through electronic means andsystems.

A trial of the hop test may be disqualified under certain circumstances.For example, the test and measurement may be disqualified if the athletedoes not begin in the proscribed initial stance as described herein. Thestance may be confirmed by another individual, by sensors, and/or basedon visual image analysis performed by a computing system.Disqualification may also result from the athlete failing to touch thebaseline with the dominant/back foot immediately prior to initiating thehop/jump, the athlete's non-dominant/lead foot landing in an orientationthat is not substantially parallel to the baseline, and/or failing tostabilize the landing leg/foot for a measurement time period (e.g., 5,10, 15, 30, 60, 120 seconds, etc.). As with the broad jump, thecountermovement lateral hop test may require the athlete to perform twosuccessful hops. The average of the distance measurements may then beused to determine the athlete's final score or value (e.g., per themethods and algorithms discussed herein) for the countermovement lateralhop test. In other arrangements, only a single successfulexercise/measurement may be required. In yet other arrangements, anynumber of measurements may be required (e.g., 3, 5, 10, 12, etc.).

A further measure of golf athleticism may include a wood-chop bounceexercise/test. A wood-chop bounce may include an athlete performing across-body rotational throw or slam. The throw or slam may be performeddiagonally downwards (e.g., cross-body) with both hands on a thrownobject (e.g., a ball). FIGS. 12A-12C illustrate an example motion forperforming the wood-chop bounce. In FIG. 12A, for example, the athlete1201 assumes an initial stance and position along a baseline 1203. Aswith the countermovement lateral hop, the athlete may be required toplace his or her dominant foot on the baseline 1203 with the width ofhis or her body perpendicular to the baseline 1203. Again, varioussensors and computing systems or devices may be used to confirm that theathlete 1201 is in the correct stance and position. For example, ball1205 may include sensors to detect whether the athlete is touching twopoints on the ball 1205 (e.g., representing that the user is using bothhands to grasp the ball).

The athlete may next be instructed to draw the ball up and back (e.g.,just above head level) and to slam or throw the ball cross-body downwardand toward the ground as shown in FIG. 12B. The goal of throwing theball in this manner may be to achieve a maximum bounce and farthestsecond bounce or touch point. In the illustrated example, the athletemay be instructed to throw the ball 1205 toward a designated point 1207.In a particular arrangement, point 1207 may be five feet from thebaseline (in a widthwise direction of the athlete when in the initialstance). In some examples, ball 1205 may be required to take the initialbounce within a testing field. In a particular example, the testingfield may be 10 feet wide (e.g., baseline 1203 may be 10 feet wide).

FIG. 12C illustrates ball 1205 and athlete 1201 after the ball 1205 hasmade an initial bounce (e.g., near or at the predefined point 1207). Onthe second bounce of ball 1205, a marker may be placed or the positionmay be recorded. In one example, an electronic detection system may useweight sensors or RFID tags to determine a second bounce landing point.RFID tags may be incorporated into the ball 1205 or other thrown object.The second bounce point might also be required to be within the testingfield (e.g., within an area that is ten feet wide). A distance betweenthe baseline 1203 and the second bounce landing point may be measuredand recorded. The measured distance may then be used as a basis fordetermining a user's score or athleticism rating in the wood-chop bounceexercise or test.

The wood-chop bounce test includes various situations in which atest/measurement may be disqualified and the test results not recorded.For example, if the ball fails to land within the test field, the trialmay be disqualified. In other examples, disqualification may result ifthe athlete does not begin the test in a golf stance with thedominant/back foot touching the baseline, the athlete does not throw theball with two hands cross-body (e.g., the athlete might not be permittedto turn, open and square to the fairway when throwing), and/or the ballis bounced beyond the predefined first bounce point (e.g., striking theground further than five feet or other predefined distance from thebaseline). Various other disqualification rules may also be used inaddition or as an alternative to any of the above noted disqualificationcriteria.

An alternate or additional version of the wood-chop bounce may involveneutralizing hip movement so that an athlete does not rely on hipmovement in performing the test (e.g., throwing the ball). In oneexample, the athlete may be required to place and hold a ball or otherobject between his or her legs (e.g., above the knees). When throwing,the athlete is required to maintain his or her hold of the objectbetween his or her legs. By having such a requirement, the test mayminimize the contribution of hip movement during the throw. The ballheld between the athlete's legs may be different in size, shape, color,weight and the like from the ball thrown. In another example, the ballheld between the athlete's legs may be the same in size, shape, color,weight and other attributes as the ball to be thrown.

Another test that may be used to evaluate golf athleticism is aside-sling object launch exercise. This test or exercise may be used toevaluate an athlete's arm swing power while in a particular stance orposition. The side-sling object launch may be performed in a hip-neutralmanner as is further described below. FIGS. 13A-13D illustrate themovements associated with the side-sling object launch. In FIG. 13A, forexample, the athlete 1301 may be instructed to take an initialposition/stance similar to a golf stance. For example, the user'sdominant foot 1303 may be positioned on a baseline 1305 of a test field1311 and the athlete's body may be positioned width-wise perpendicularto baseline 1305. The athlete 1301 may further be required to hold anobject (such as a ball 1307) between his or her legs to reduce hipmovement contributions to the athlete's side-sling. In particular, theathlete 1301 may be required to hold the object between his or her legs(e.g., above the knees) through the entire exercise.

FIG. 13B illustrates athlete 1301 holding another object (e.g., ball1309) that is to be thrown down a test field 1311 in direction C. Insome arrangements, ball 1307 may be different in size, shape, color,weight and the like from ball 1309. In another example, ball 1307 may beidentical to ball 1309. In FIG. 13C, the athlete 1301 is shown slingingball 1309 down the test field 1311. The throw may be a singleunderhanded throw and may require the user to start by swinging his orher arm 1313 ball directly back and then slinging his or her arm 1313forward, releasing the ball out into the test field 1311. The athlete1301 may be required to follow through with the swing, ending upright asshown in FIG. 13D.

Upon completion of the throw, a distance between the baseline 1305 andthe initial landing/contact point of the thrown object, e.g., ball 1309,may be measured. The distance may correspond to the perpendiculardistance between the baseline 1305 and the ball 1309. This distance maythen be used to determine the athlete's athleticism score or value forthe side-sling object launch exercise. Multiple trials may be performedand an average may be taken in some arrangements. Disqualifications maybe levied if the athlete 1301 throws the ball 1309 and the ball 1309does not land within the test field 1311 (width-wise), the athlete 1301does not begin the test in the initial position (e.g., golf stance) withhis or her back foot 1303 touching baseline 1305, the athlete'sbackswing carries his or her arm 1313 outside of his width-wise bodyline (e.g., the arm 1313 crosses the plane created by the athlete'sshoulders and back in the initial stance, causing the ball 1309 todeviate from the test field 1311), the athlete 1301 takes any kind ofstep with his front foot and/or if ball 1307 held between the athlete'slegs falls out during the throw.

In one or more of the above tests, RFID tags or other sensors may alsobe worn by the user to detect various movements and positions. Forexample, an RFID tag may be placed in heel portion of a user's shoe todetect a landing position in the broad jump test. In another example,RFID tags may be incorporated into a lateral edge (inner and/orexterior) of a user's shoe to detect a landing point in thecountermovement lateral hop test. The RFID tag in the lateral edge or inother portions of the shoe may also be used to detect whether the usercontacted or is contacting a baseline.

As with the par 5 step test, a computing system such as processingdevice 106 or computer system 108 may provide automated instructions tothe athletes for any of the above noted exercises and movements,positions, measurements and data submissions described herein. Forexample, the computing system may provide audio, visual and/or hapticcues. Additionally or alternatively, sensors may be used to determine ifthe athlete is in a correct stance, determine one or more landingpositions of a thrown object or the athlete, positions of an athlete'sbody parts and the like. The computing system may further generate adata input form requesting recordation of trial data for each of thetests described herein. Alternatively or additionally, the computingsystem may generate a single form or a sequence of forms having fieldsfor the types of data to be recorded for each of the various golfathleticism tests/exercises. Upon receipt of the data, the computingsystem may determine the rating or score for each exercise in additionto an overall golf athleticism rating that takes into account all of thescores and results from all of the tests/exercises performed. Forexample, as described herein, an athlete's fractional event points (orother scoring value) for each text/exercise may be summed to result inan overall rating. The overall rating may also be subject to scalingfactors (e.g., multiplying by a certain factor) to derive the scaledathleticism rating.

FIGS. 14A and 14B illustrate an example test field configuration thatmay be used for one or more of the golf athleticism rating testsdescribed herein. FIG. 14A illustrates a front perspective view of testfield 1400. Test field 1400 may include multiple markers including5-foot markers 1403 and submarkers 1405. A baseline 1407 may be definedat the O-foot marker 1403 a with a staging area 1409 definedtherebehind. The test field 1400 may be divided width-wise into twosections 1411 a and 1411 b by a demarcation or dividing line 1413.Section 1411 a may be configured for throwing-oriented exercises whilesection 1411 b may be configured for jumping/hopping typetests/exercises. In one arrangement, section 1411 b might only extendlength-wise for a distance smaller than the length of section 1411 a. Inparticular, section 1411 b might only have distance markers up to afirst distance while section 1411 a may have distance markers up to asecond distance greater than the first distance. In a specific example,section 1411 a may be 50 feet long while section 1411 b may be 10 feetlong. Other distances may be used to define each of sections 1411 a and1411 b. The widths of sections 1411 a and 1411 b may be equal or one maybe greater than the other. In one particular example, the width ofsection 1411 a may be 10 feet.

FIG. 14B illustrates test field 1400 from a top down view. Test field1400, as described, includes sections 1411 a and 1411 b that aresubstantially rectangular. In section 1411 a, a bounce line for varioustests such as the wood-chop bounce may be predefined at the 5 footmarker 1403 b. The remaining portion of section 1411 a may be labeledwith a “FAIRWAY” mark to indicate the throwing region. Section 1411 b,on the other hand, may be labeled with a “JUMP ZONE” label to identifysection 1411 b as a jumping or hopping test area. Using these predefinedsections 1411 a and 1411 b, athletes may perform different tests at thesame time.

In one or more arrangements, test field 1400 may be provided as a matthat is portable. The portable mat may allow test administrators andtest takers to administer or take the tests in a variety of locations(i.e., the tests would not be restricted to one particular physicallocation). Additionally, using a portable mat may provide consistency inthe results that are produced. In some arrangements, the mat may includeone or more electronic devices including sensors, LED displays, othervisual displays, haptic feedback devices and the like. For example, LEDnumbering may be used instead of drawn numbering on the mat. In anotherexample, weight sensors may be used to detect the position and weightdistribution of athletes and test objects (e.g., balls). In a particularexample, a sensor may be placed at the borders of the test sections 1411a and 1411 b including the baseline 1407, end lines 1405 a and 1405 band dividing line 1413. In yet other examples, infrared or laser sensorsmay be used to detect whether an athlete or an object is touching (ornot touching) or touches a particular point on the mat such as thebounce line, the baseline and the like. In still another example, adisplay device may display instructions for performing a test. The matmay thus further include data transmission devices (e.g., wirelessadapters, USB ports, serial ports and the like) to transmit detectedinformation to one or more computing systems such as processing device106 and/or computer system 108. The baseline, bounce line and otherdemarcations on the mat may be provided in different colors or patternsfor visual differentiation. This may help the athlete identify targets,position requirements and the like.

The mat or portable test field may be composed of various materialsand/or combinations of materials including plastic such as artificialturf and/or, foams, metals and the like. The mat may, in one particularexample, be roughly 15 feet wide and 60 feet long. Thus, in the exampledescribed above where section 1411 a (FIGS. 14A and 14B) is 10 feetwide, the other section, section 1411 b, may be 5 feet wide or smaller.Other lengths and widths may be used depending on the test criteria andrequirements.

While the invention has been described in detail in terms of specificexamples including presently preferred modes of carrying out theinvention, those skilled in the art will appreciate that there arenumerous variations and permutations of the above described systems andmethods. Thus, the scope of the invention should be construed broadly asset forth in the appended claims.

1. A method comprising: receiving, at a computing system having at leastone processor, athletic performance results from multiple types ofperformance tests, the athletic performance results including at leasttwo selected from the following: a change in pulse of an athletemeasured during a stepping exercise, a broad jump distance of anathlete, a lateral hop distance of an athlete, a bounce distance of aball when thrown by the athlete in a downward direction toward a target,and a sling distance of a ball when thrown by the athlete using aunderhanded side sling; and generating, by the computing system, a golfathleticism rating based on the at least two athletic performanceresults.
 2. The method of claim 1, wherein the athletic performanceresults includes the thrown distance of the ball, and wherein the methodfurther includes receiving, at the computing system, the sling distanceof the ball during an exercise in which the athlete holds an objectbetween the athlete's legs while performing the underhanded side sling.3. The method of claim 1, wherein the stepping exercise includesmultiple rounds of stepping by the athlete, each round of steppingfollowed by a rest period.
 4. The method of claim 1, further comprisinggenerating an athleticism score for each athleticism performance result,and wherein generating the golf athleticism rating includes combiningeach athleticism score.
 5. The method of claim 4, wherein generating theathleticism score for each athletic performance result includesnormalizing the athletic performance result data to a common scale. 6.The method of claim 1, wherein at least one of the athletic performanceresults is received from an athletic performance field having one ormore integrated sensors.
 7. The method of claim 6, wherein the athleticperformance field comprises a portable test field.
 8. An apparatuscomprising: at least one processor; and memory operatively coupled tothe at least one processor and storing computer readable instructionsthat, when executed, cause the apparatus to: receive athleticperformance results corresponding to an athlete's performance duringmultiple types of athletic exercises, the athletic performance resultsincluding at least two of: a change in pulse of an athlete measuredduring a stepping exercise, a broad jump distance of an athlete, alateral hop distance of an athlete, a bounce distance of a ball whenthrown by the athlete in a downward direction toward a target, and asling distance of a ball when thrown by the athlete using a underhandedside sling; and generate a golf athleticism rating based on the at leasttwo athletic performance results.
 9. The apparatus of claim 8, whereinthe athletic performance results includes the sling distance of theball, and wherein the method further includes receiving, at thecomputing system, the sling distance of the ball during an exercise inwhich the athlete holds an object between the athlete's legs whileperforming the underhanded single-hand throw.
 10. The apparatus of claim8, wherein the stepping exercise includes multiple rounds of stepping bythe athlete, each round of stepping followed by a rest period.
 11. Theapparatus of claim 8, further comprising computer readable instructionsfor generating an athleticism score for each athletic performanceresult, and wherein generating the golf athleticism rating includescombining the athleticism scores.
 12. The apparatus of claim 11, whereingenerating each athleticism score includes normalizing the athleticismresult to a common scale.
 13. The apparatus of claim 8, wherein at leastone of the athletic performance results is received from an athleticperformance field having one or more integrated sensors.
 14. Theapparatus of claim 13, wherein the athletic performance field comprisesa portable test field.
 15. One or more non-transitory computer readablemedia having computer-executable instructions embodied thereon that whenexecuted by a processor perform a method for evaluating the athleticismof an athlete in golf, the method comprising: receiving at least tworesults for the athlete's performance in at least two different athleticperformance tests related to golf; comparing each of the at least tworesults to a corresponding distribution of test results of athletic datafor athletes similar to the athlete and determining a percentile rankingfor each of the at least two results; transforming the percentileranking for each of the at least two results to a fractional event pointnumber for each result, wherein the percentile rankings for each of theat least two results are progressive; and determining an athleticismrating score for the athlete in golf based on the fractional event pointnumbers.
 16. The one or more non-transitory computer readable media ofclaim 15, further comprising determining an athleticism score includescombining the fractional event point numbers to determine a combinedfractional event point number and applying a scaling factor to thecombined fractional event point number.
 17. The one or morenon-transitory computer readable media of claim 16, wherein transformingthe percentile ranking for the at least two results to the fractionalevent point number comprises applying an inverse-Weibull transformation.18. The one or more non-transitory computer readable media of claim 17,wherein the distribution of test results of athletic data for athletessimilar to the athlete is determined using the empirical cumulativedistribution function.
 19. The one or more non-transitory computerreadable media of claim 18, wherein the percentile ranking for each ofthe at least two results is capped at a ceiling value.
 20. The one ormore non-transitory computer readable media of claim 15, wherein theathletic performance results including at least two of: a change inpulse of an athlete measured during a stepping exercise, a broad jumpdistance of an athlete, a lateral hop distance of an athlete, a bouncedistance of a ball when thrown by the athlete in a downward directiontoward a target, and a sling distance of a ball when thrown by theathlete using a underhanded side sling.